Introduction to FedData

FedData is a package for downloading data from federated (usually US Federal) data sets, using a consistent, spatial-first API. In this vignette, you’ll learn how to load the FedData package, download data for an “template” area of interest, and make simple web maps using the mapview package.

Load FedData and define a study area

# Load FedData and magrittr
library(FedData)
library(magrittr)
library(terra)

# Install mapview if necessary
if (!require("mapview")) {
  install.packages("mapview")
}

library(mapview)
mapviewOptions(
  basemaps = c(),
  homebutton = FALSE,
  query.position = "topright",
  query.digits = 2,
  query.prefix = "",
  legend.pos = "bottomright"
)

# Create a nice mapview template
plot_map <-
  function(x, ...) {
    if (inherits(x, "SpatRaster")) {
      x %<>%
        as("Raster")
    }

    bounds <-
      FedData::meve %>%
      sf::st_bbox() %>%
      as.list()

    mapview::mapview(x, ...)@map %>%
      leaflet::removeLayersControl() %>%
      leaflet::addTiles(
        urlTemplate = "https://basemap.nationalmap.gov/ArcGIS/rest/services/USGSShadedReliefOnly/MapServer/tile/{z}/{y}/{x}"
      ) %>%
      leaflet::addProviderTiles("Stamen.TonerLines") %>%
      leaflet::addProviderTiles("Stamen.TonerLabels") %>%
      leaflet::addPolygons(
        data = FedData::meve,
        color = "black",
        fill = FALSE,
        options = list(pointerEvents = "none"),
        highlightOptions = list(sendToBack = TRUE)
      ) %>%
      leaflet::fitBounds(
        lng1 = bounds$xmin,
        lng2 = bounds$xmax,
        lat1 = bounds$ymin,
        lat2 = bounds$ymax
      )
  }


# FedData comes loaded with the boundary of Mesa Verde National Park, for testing
FedData::meve
#> Geometry set for 1 feature 
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -108.5547 ymin: 37.15642 xmax: -108.3396 ymax: 37.35052
#> Geodetic CRS:  WGS 84

plot_map(FedData::meve,
  legend = FALSE
)

Datasets

USGS National Elevation Dataset

# Get the NED (USA ONLY)
# Returns a raster
NED <- get_ned(
  template = FedData::meve,
  label = "meve"
)

plot_map(NED,
  layer.name = "NED Elevation (m)",
  maxpixels = terra::ncell(NED)
)

ORNL Daymet

# Get the DAYMET (North America only)
# Returns a raster
DAYMET <- get_daymet(
  template = FedData::meve,
  label = "meve",
  elements = c("prcp", "tmax"),
  years = 1980:1985
)

plot_map(DAYMET$tmax$`1985-10-23`,
  layer.name = "TMAX on 23 Oct 1985 (ºC)",
  maxpixels = terra::ncell(DAYMET$tmax)
)

NOAA GHCN-daily

# Get the daily GHCN data (GLOBAL)
# Returns a list: the first element is the spatial locations of stations,
# and the second is a list of the stations and their daily data
GHCN.prcp <- get_ghcn_daily(
  template = FedData::meve,
  label = "meve",
  elements = c("prcp")
)
#> Warning: attribute variables are assumed to be spatially constant throughout
#> all geometries
#> Warning in CPL_write_ogr(obj, dsn, layer, driver,
#> as.character(dataset_options), : GDAL Error 1:
#> /tmp/RtmpeU5ZFn/FedData/extractions/ghcn/meve/meve_GHCN_stations.shp does not
#> appear to be a file or directory.

plot_map(GHCN.prcp$spatial,
  label = GHCN.prcp$spatial %$%
    paste0(ID, ": ", NAME),
  legend = FALSE
)

Standardized data

# Elements for which you require the same data
# (i.e., minimum and maximum temperature for the same days)
# can be standardized using standardize==T
GHCN.temp <- get_ghcn_daily(
  template = FedData::meve,
  label = "meve",
  elements = c("tmin", "tmax"),
  years = 1980:1985,
  standardize = TRUE
)

plot_map(GHCN.temp$spatial,
  label = GHCN.temp$spatial %$%
    paste0(ID, ": ", NAME),
  legend = FALSE
)

USGS National Hydrography Dataset

# Get the NHD (USA ONLY)
NHD <-
  get_nhd(
    template = FedData::meve,
    label = "meve"
  )

# FedData comes with a simple plotting function for NHD data
plot_nhd(NHD, template = FedData::meve)

# Or, do an interactive map
NHD[purrr::map_lgl(NHD, ~ (nrow(.x) != 0))] %>%
  plot_map()

# You can also retriev the Watershed Boundary Dataset
WBD <-
  get_wbd(
    template = FedData::meve,
    label = "meve"
  )

plot_map(WBD,
  zcol = "name",
  legend = FALSE
)

USDA NRCS SSURGO

# Get the NRCS SSURGO data (USA ONLY)
SSURGO.MEVE <- get_ssurgo(
  template = FedData::meve,
  label = "meve"
)

SSURGO.MEVE$spatial %>%
  dplyr::left_join(
    SSURGO.MEVE$tabular$mapunit %>%
      dplyr::mutate(mukey = as.character(mukey)),
    by = c("MUKEY" = "mukey")
  ) %>%
  dplyr::mutate(label = paste0(MUKEY, ": ", muname)) %>%
  plot_map(
    zcol = "label",
    legend = FALSE
  )

SSURGO by Soil Survey Area

# Or, download by Soil Survey Area names
SSURGO.areas <- get_ssurgo(
  template = c("CO670"),
  label = "CO670"
)

SSURGO.areas$spatial %>%
  dplyr::left_join(
    SSURGO.areas$tabular$muaggatt %>%
      dplyr::mutate(mukey = as.character(mukey)),
    by = c("MUKEY" = "mukey")
  ) %>%
  dplyr::mutate(label = paste0(MUKEY, ": ", muname)) %>%
  plot_map(
    zcol = "brockdepmin",
    layer.name = "Minimum Bedrock Depth (cm)",
    label = "label"
  )